@inproceedings{46a6fdfaefce4d41ad2019c2c92e5c8b,
title = "The potential method for price-formation models",
abstract = "We consider the mean-field game price formation model introduced by Gomes and Sa{\'u}de. In this MFG model, agents trade a commodity whose supply can be deterministic or stochastic. Agents maximize profit, taking into account current and future prices. The balance between supply and demand determines the price. We introduce a potential function that converts the MFG into a convex variational problem. This variational formulation is particularly suitable for machine learning approaches. Here, we use a recurrent neural network to solve this problem. In the last section of the paper, we compare our results with known analytical solutions.",
keywords = "Lagrange multiplier, Mean Field Games, Potential Function, Price formation",
author = "Yuri Ashrafyan and Tigran Bakaryan and Diogo Gomes and Julian Gutierrez",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 61st IEEE Conference on Decision and Control, CDC 2022 ; Conference date: 06-12-2022 Through 09-12-2022",
year = "2022",
doi = "10.1109/CDC51059.2022.9992621",
language = "English (US)",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7565--7570",
booktitle = "2022 IEEE 61st Conference on Decision and Control, CDC 2022",
address = "United States",
}